Saldelder, F, Yuval, O, Ilett, TP et al. (3 more authors) (2021) Markerless 3D spatio-temporal reconstruction of microscopic swimmers from video. In: Visual observation and analysis of Vertebrate And Insect Behavior 2020. 25th International Conference on Pattern Recognition (ICPR 2020), 10-15 Jan 2021, Milan, Italy / online.
Abstract
3D object reconstruction of deformable objects is a long standing challenge for computer vision. Here we develop a system for the 3D reconstruction of a single marker-less object – a freely moving biological swimmer in 3D space – using a passive, fixed-camera set-up. We focus on microscopic, long and thin (1 mm long, 80 µm thick) roundworms. Our set-up provides the resolution required both to track the animal’s coordinates across a large volume and to reconstruct its 3D posture at every frame. A data-pipeline is presented which combines model calibration, 2D image analysis and 3D reconstruction of the body midline, representing the complete posture up to orientation and internal twist. We present results, validation and open challenges, including instances of occlusion due to insufficient projected information, and experimental limitations of resolution and focus.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number Leverhulme Trust ECF-2017-591 EPSRC (Engineering and Physical Sciences Research Council) EP/J004057/1 EPSRC (Engineering and Physical Sciences Research Council) EP/S01540X/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Nov 2020 11:21 |
Last Modified: | 05 Mar 2021 10:48 |
Published Version: | https://homepages.inf.ed.ac.uk/rbf/vaib20.html |
Status: | Published |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:168497 |